Article Tools

Abstract

Mutual information (MI) based image registration has been found to be quite effective in many medical image applications. However, standard MI hampers the convergence of registration transformation parameters since it contains local maxima. In this paper, a novel registration method is proposed. At first, MI based on edge width matching is computed to avoid great change of joint probability distribution and get less local maxima. Particle swarm optimization (PSO), which combines local search methods with global ones balancing exploration and exploitation, is done to search the optimal registration parameter. PSO has less computational complexity as its complex behavior follows only a few simple rules. It could avoid local maxima and reach global optimal results. This method is applicable to a variety of multimodal images, and suitable to different interpolation methods. Theoretical analysis and experiments show that this method is effective and accurate to register multimodal medical images.

Cited By

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.